• Structural Engineering and Mechanics
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• v.16 no.1
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• pp.17-34
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• 2003

This paper presents a damage assessment procedure applied to periodic spring mass systems using an eigenvalue sensitivity-based method. The damage is directly related to the stiffness reduction of the damage element. The natural frequencies of periodic structures with one single disorder are found by adopting the transfer matrix approach, consequently, the first order approximation of the natural frequencies with respect to the disordered stiffness in different elements is used to form the sensitivity matrix. The analysis shows that the sensitivity of natural frequencies to damage in different locations depends only on the mode number and the location of damage. The stiffness changes due to damage can be identified by solving a set of underdetermined equations based on the sensitivity matrix. The issues associated with many possible damage locations in large structural systems are addressed, and a means of improving the computational efficiency of damage detection while maintaining the accuracy for large periodic structures with limited available measured natural frequencies, is also introduced in this paper. The incomplete measurements and the effect of random error in terms of measurement noise in the natural frequencies are considered. Numerical results of a periodic spring-mass system of 20 degrees of freedom illustrate that the proposed method is simple and robust in locating single or multiple damages in a large periodic structure with a high computational efficiency.

• Proceedings of the Korean Magnestics Society Conference
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• 2015.05a
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• pp.30-31
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• 2015

• Proceedings of the Zoological Society Korea Conference
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• 2000.10a
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• pp.156.2-157
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• 2000

No Abstract, See Full Text

• Advanced Composite Materials
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• v.16 no.4
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• pp.299-314
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• 2007

In the present study, natural fibers (jute, kenaf and henequen) reinforced thermoplastic (poly(lactic acid) and polypropylene) and thermosetting (unsaturated polyester) matrix composites were well fabricated by a compression molding technique using all chopped natural fibers of about 10 mm long, respectively. Prior to green composite fabrication, natural fiber bundles were surface-treated with tap water by static soaking and dynamic ultrasonication methods, respectively. The interfacial shear strength, flexural properties, and dynamic mechanical properties of each green composite system were investigated by means of single fiber microbonding test, 3-point flexural test, and dynamic mechanical analysis, respectively. The result indicated that the properties of the polymeric resins were significantly improved by incorporating the natural fibers into the resin matrix and also the properties of untreated green composites were further improved by the water treatment done to the natural fibers used. Also, the property improvement of natural fiber-reinforced green composites strongly depended on the treatment method. The interfacial and mechanical results agreed with each other.

• The Journal of Korea Robotics Society
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• v.14 no.1
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• pp.22-30
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• 2019

For effective human-robot interaction, robots need to understand the current situation context well, but also the robots need to transfer its understanding to the human participant in efficient way. The most convenient way to deliver robot's understanding to the human participant is that the robot expresses its understanding using voice and natural language. Recently, the artificial intelligence for video understanding and natural language process has been developed very rapidly especially based on deep learning. Thus, this paper proposes robot vision to audio description method using deep learning. The applied deep learning model is a pipeline of two deep learning models for generating natural language sentence from robot vision and generating voice from the generated natural language sentence. Also, we conduct the real robot experiment to show the effectiveness of our method in human-robot interaction.

• Journal of the Korean Wood Science and Technology
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• v.51 no.6
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• pp.481-492
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• 2023

The ecofriendly lifestyle has attracted considerable support for sustainable development. Natural dyes, as sustainable products, have become a research focus and development area for many scientists. Ecofriendly processing also supports circular sustainable development. This study effectively obtained tannins as a natural dye from merbau (Intsia bijuga) sawdust using water as an ecofriendly solvent. Merbau sawdust is an underutilized industrial waste. Temperature and solid-solvent ratio variations were performed to extract tannins from merbau sawdust. Temperature and solid-solvent ratio positively affected solution yield and tannin concentration. The optimal condition was identified using response surface methodology and experimental observations. A yield of 0.2217 g tannins/g merbau was obtained under the conditions of 333.15 K and 0.125 solid-solvent ratio. Extraction was controlled by convective mass transfer at the interface of solid particles.

• Smart Structures and Systems
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• v.31 no.2
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• pp.141-154
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• 2023

After an earthquake, information regarding potential damage to buildings close to the epicenter is very important during the initial emergency response. This study proposes the use of crowdsourced measured acceleration response data collected from smartphones located within buildings to perform system identification of building structures during earthquake excitations, and the feasibility of the proposed approach is studied. The principal advantage of using crowdsourced smartphone data is the potential to determine the condition of millions of buildings without incurring hardware, installation, and long-term maintenance costs. This study's goal is to assess the feasibility of identifying the lowest fundamental natural frequencies of buildings without knowing the orientations and precise locations of the crowds' smartphones in advance. Both input-output and output-only identification methods are used to identify the lowest fundamental natural frequencies of numerical finite element models of a real building structure. The effects of time synchronization and the orientation alignment between nearby smartphones on the identification results are discussed, and the proposed approach's performance is verified using large-scale shake table tests of a scaled steel building. The presented results illustrate the potential of using crowdsourced smartphone data with the proposed approach to identify the lowest fundamental natural frequencies of building structures, information that should be valuable in making emergency response decisions.

• Nuclear Engineering and Technology
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• v.50 no.7
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• pp.1079-1087
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• 2018

There are many parameters that affect the natural circulation flow, such as height difference, heating power size, pipe diameter, system pressure and inlet temperature and so on. In general analysis the heating power is often regarded as a uniform distribution. The ANSYS-CFX numerical analysis software was used to analyze the flow heat transfer of supercritical water under different heating power distribution conditions. The distribution types of uniform, power increasing, power decreasing and sine function are investigated. Through the analysis, it can be concluded that different power distribution has a great influence on the flow of natural circulation if the total power of heating is constant. It was found that the peak flow of supercritical water natural circulation is maximal when the distribution of heating power is monotonically decreasing, minimal when it is monotonically increasing, and moderate at uniform or the sine type of heating. The simulation results further reveal the supercritical water under different heat transfer conditions on its flow characteristics. It can provide certain theory reference and system design for passive residual heat removal system about supercritical water.

• Proceedings of the Korean Magnestics Society Conference
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• 2015.05a
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• pp.32-33
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• 2015

• Journal of the Korean Society of Visualization
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• v.14 no.3
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• pp.46-50
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• 2016

The objective of the present study is to perform experiments for water filled cavity heated and cooled from the side at $Ra=8.5{\times}108$. This experiment can provide validation database of the standard k-${\varepsilon}$ turbulence model for single-phase turbulent natural convection which has been regarded as one of the important phenomena in nuclear safety. For the natural convection inside a cavity, temperature and velocity were obtained by thermometry and PIV (Particle Image Velocimetry) methods. These results would be used for validation of standard k-${\varepsilon}$ turbulence model.